import torch
from torch.utils.data import Dataset
from PIL import Image

class My_Dataset(Dataset):
    """自定义数据集"""

    def __init__(self,image_path,image_class,transform=None):
        self.image_path = image_path
        self.image_class = image_class
        self.transform = transform

    def __len__(self):
        return len(self.image_path)

    def __getitem__(self, item):
        img = Image.open(self.image_path[item])
        if img.mode!='RGB':
            img = img.convert("RGB")
        label = self.image_class[item]
        if self.transform is not None:
            img = self.transform(img)
        return img,label

    @staticmethod
    def collate_fn(batch):
        # 官方实现的default_collate可以参考
        # https://github.com/pytorch/pytorch/blob/67b7e751e6b5931a9f45274653f4f653a4e6cdf6/torch/utils/data/_utils/collate.py
        images, labels = tuple(zip(*batch))

        images = torch.stack(images, dim=0)
        labels = torch.as_tensor(labels)
        return images, labels
